Finally, we present exhaustive top-1 classification accuracy results on the CIFAR-10 dataset for a variety of gradient distortion attacks coupled with choice/behavior patterns of the adversarial nodes. Our results indicate an average 30% accuracy increase on large scale image classification training (CIFAR-10) [1]} under the most sophisticated attacks. In summary, the performance gap between Aspis and other methods is especially stark in the strong attack scenario.
